1. Field of the Invention
This invention relates generally to a Doppler type ultrasound diagnostic apparatus to obtain dynamic color information of blood flows in a living body and, more particularly, to a Doppler type ultrasound diagnostic apparatus in which filter transient response characteristics are improved to eliminate from the dynamic color information various clutter components caused by reflections from internal organs such as myocardia.
2. Discussion of the Background
The color Doppler ultrasound diagnostics is an indirect diagnostic method of obtaining dynamic information of blood flows in a subject body by using ultrasound Doppler effect. Remarkable progress has been made in ultrasound diagnostic apparatus for carrying out this diagnostic method.
A ultrasound diagnostic apparatus implemented with color Doppler tomography (also referred to as "color flow mapping" (CFM)) is one of the above-mentioned diagnostic apparatus. Color Doppler tomography, or CFM, is an application of a technique used in the field of radar technology called moving target indication (MTI). CFM provides a two dimensional distribution image of blood velocity in a tomographic plane.
In order to obtain this two dimensional image, ultrasound echo signals reflecting from a subject body in response to transmitting ultrasound pulses are converted into electronic signals which are in turn divided into two components, i.e., real and imaginary parts. Both the real and imaginary parts of the echo signals are phase-detected in accordance with a reference signal through a phase detector from which Doppler signals indicative of phase shifts are derived from the reference signal. The real and imaginary parts of the Doppler signals are temporarily stored in a buffer memory after being converted into respective digital data with an A/D converter.
In the case of CFM, a plurality of transmitting and receiving ultrasound pulses are repeated N times, e.g., 16 times, in a same scanning line direction. As a result, digital Doppler data necessary for reconstruction of a video image is received as first through third dimensional data for each of the real and imaginary parts and the received data is stored in a buffer memory of an MTI filter. The first through third dimensional data represent the number of scanning lines (scanning line number), that of pixel in a depth direction of each scanning line (pixel number), and that of Doppler data for each pixel obtained by repetition of transmitting and receiving ultrasound pulses (Doppler data number), respectively.
At an identical sample position of a scanning sectional plane, receiving echoes can be obtained in a time sequential manner by repeating transmitting and receiving ultrasound pulses N times. Digital data phase-detected on the basis of the received echoes are disposed in the third dimensional direction. A signal variation velocity taken in the third dimensional direction corresponds to a size of Doppler shift frequencies, or that of a target moving velocity.
Third dimensional data (Doppler signals) received and stored in a buffer memory of an MTI filter are subject to filtering of clutter components in every data row in the third dimensional direction of each pixel position. The following is the principle of this filtering.
Echo signals from objects like blood corpuscles moving more rapidly than a certain velocity are mixed with signals from tissues, for instance, internal organs in the receiving echoes (called clutter components). The signal intensity of the clutter components is greater by about 40 dB through 80 dB than that of the echo signals from the blood corpuscles but the moving velocity of the latter is greater than that of the former. A filter circuit of the MTI filter is comprised of a high pass filter, the cut-off frequency of which is set up to eliminate the clutter components. The echo signals from the blood corpuscles are derived from the detected Doppler signals after elimination of the clutter components through the high pass filter.
The echo signals thus derived are then provided to another process for inferences of the blood corpuscle physical states (average blood flow velocity, power, distribution, etc.) and a two dimensional image is formed based upon such inferences.
As an example of an MTI filter to eliminate such clutter components as set forth above, an indefinite-duration impulse-response (II) type high pass filter is shown in FIG. 9 is provided. Generally, however, artificially high frequency signals appear on time-based waveforms of the high pass filters outputs at the start of Doppler signal, causing the filtering operations to not perform as expected. This results from transient responses due to finite data sequences passing through the filter.
These transient responses may be explained as follows. When a first of a plurality of Doppler data signals is provided to the high pass filter, a latch circuit T is in a reset state into which zero is entered as a value. Entry data into the latch circuit changes the latch value from zero to certain values (mainly clutter component values) so rapidly that a transient response is caused.
Another explanation of the transient response is now provided. Prior to a starting point, all latch circuits of the high pass filter represent zero values. This state of all zeros is shown in FIG. 20(a) by way of example. Since a discontinuous waveform appearing at a time starting point includes high frequency components, the transient response may be considered to be a phenomenon in which an influence caused by discontinuity of the starting point take place through an impulse response of the high pass filter. When Doppler data sequences with step-like discontinuity at the starting point pass through the high pass filter as shown in FIG. 20(a), high frequency components are added to its time-base waveform as shown in FIG. 20(b) because of the transient response. The high frequency components do not properly reflect blood flow dynamics because of error factors present. Therefore, any inference based upon output signals of the high pass filter at this point has poor reliability, and a final image displayed in accordance with the high frequency components cannot be accepted as a correct image of blood flows.
One technique to exclude the error factors due to the transient response is to eliminate from the filter output data a plurality of Doppler data which range from the time-base starting point to a predetermined number of sampling points, and further removing sampling points in which the high frequency components caused by discontinuity appear in the Doppler signals with N Doppler data. In the case, however, the number of Doppler data is reduced, and the inferential arithmetic operation accuracy of an averaged blood flow velocity becomes poor. In addition, initial sampling data at N points become meaningless and the property of real time is less advantageous despite a significant increase in accuracy of the inferential arithmetic operation. Thus, there are certain limitations on the number of Doppler data which can be removed from output data of the filter, however, the less data removed in accordance with the above described technique, the worse an influence on that data resulting from the transient response.
Generally, the countermeasure for the transient response has been carried out in an initial value subtraction process as set forth in Japanese Unexamined Patent Publication (Tokkai Sho) 63-84532. According to its description, an amplitude value of Doppler data at the time-base starting point is made use of as an initial data point and it is subtracted from each of subsequent Doppler data points. When this process is carried out, the time-base waveform shown in FIG. 20(a) is converted into the one shown in FIG. 20(c) so that the discontinuity, i.e., the step-like rapid change of data sequence at the time-base starting point can be eased. The Doppler data sequence processed in this way (Doppler signals) are entered into the high pass filter where the filtering process is applied.
According to the initial value subtraction process, the discontinuity at the starting point can be eased but it cannot be perfectly removed. As shown in FIG. 20(c), a discontinuity is still more or less left in the vicinity of the starting point and the high frequency components remain. In short, the discontinuity of a data value, per se, at the starting point is eliminated but an inclination angle .theta. indicative of a change of values at the starting point and a next sampling point cannot be avoided although data up to the starting point are substantially flat (amplitude value=0). The differential coefficient has discontinuity at the starting point which is smaller than that shown in FIG. 20(a) but the high frequency components due to the transient response appear similarly to those set forth above in the time-base output waveform of the high pass filter. It brings about the following disadvantage.
A signal sampling interval .DELTA.T and a Nyquist frequency fn have the following relationship: EQU .DELTA.T=1/(2fn) (1)
If a velocity of blood flow of interest is relatively fast, it is necessary to set the Nyquist frequency fn to be high and the sampling interval .DELTA.T becomes short. However, in a case where a velocity of blood flow is slow, the Nyquist frequency fn is set to be low and the sampling interval .DELTA.T becomes long.
For this reason, in the case where fast moving blood flow is tracked from Doppler signals shown in FIG. 21(a), sampling points thereof are distributed as indicated with small circles, and in the case where slow moving blood flow is tracked, sampling points are distributed as indicated with black dots. Doppler data sequences obtained through the above sampling processes are shown in FIGS. 21(b) and 21(c) for fast and slow moving blood flows, respectively.
As clear from comparison of FIGS. 21(b) and 21(c), generally, the data change rate at the starting point becomes steeper as the sampling interval is set to be longer. A transient response amplitude appearing in a waveform passing through the MTI filter (high pass filter) becomes larger in accordance with such a steep data change rate. When a slow moving blood flow is tracked, high frequency components resulting from the transient response have a great influence. The transient response is gradually smaller as a position becomes farther from the time-base starting point, but still has a level that is not negligible at the starting point. This is one of the difficulties in detecting a slow moving blood flow with high accuracy.
On the other hand, when a diagnosis object is a rather fast moving blood flow, a data value change at the starting point is made relatively small with the initial value subtraction process and the transient response influence is negligible except for Doppler data sequences at several points from the starting point. An application of a process called "an initial data cut" thereto makes it possible to discard data at several points from the beginning after filtering process and the additional high frequency components due to the transient response can be excluded.
The initial data cut process is convenient for a fast moving blood flow but it cannot be easily applied to a slow moving blood flow because inference accuracy decreases. With slow moving blood flows, an influence range due to transient responses becomes wider as time goes further from the time-base starting point. If an initial data cut is carried out, more Doppler data (initial data) will be discarded after the MTI filtering process. As the number of cut data by application of the initial data cut increases excessively and Doppler data decrease, the inference accuracy of blood flow velocity becomes lower and precise detection of blood flow information becomes more difficult. In other words, it is important to make use of as many as possible of the N sampled Doppler data so that the influence of transient responses due to clutter components can be reduced and slow velocity blood flow information can be obtained accurately. Therefore, the initial data cut process cannot be easily carried out.
Although the initial value subtraction process is, nevertheless, utilized at the present because of the reasons set forth above, the unsolved problem is the lack of elimination capability of clutter components due to transient responses for a slow velocity blood flow.